David T. Nguyen

Reducing Smartphone Application Delay through Read/Write Isolation

The smartphone has become an important part of our daily lives. However, the user experience is still far from being optimal. In particular, despite the rapid hardware upgrades, current smartphones often suffer various unpredictable delays during operation, e.g., when launching an app, leading to poor user experience. In this paper, we investigate the behavior of reads and writes in smartphones. We conduct the first large-scale measurement study on the Android I/O delay using the data collected from our Android application running on 2611 devices within nine months. Among other factors, we observe that reads experience up to 626% slowdown when blocked by concurrent writes for certain workloads. Additionally, we show the asymmetry of the slowdown of one I/O type due to another, and elaborate the speedup of concurrent I/Os over serial ones. We use this obtained knowledge to design and implement a system prototype called SmartIO that reduces the application delay by prioritizing reads over writes, and grouping them based on assigned priorities. SmartIO issues I/Os with optimized concurrency parameters. The system is implemented on the Android platform and evaluated extensively on several groups of popular applications. The results show that our system reduces launch delays by up to 37.8%, and run-time delays by up to 29.6%.

Storage-aware smartphone energy savings

In this paper, to our best knowledge, we are first to provide an experimental study on how storage techniques affect power levels in smartphones and introduce energy-efficient approaches to reduce energy consumption. We evaluate power degradation at several layers of block I/O, focusing on the block layer and device driver. At each level, we investigate the amount of energy that can be saved, and use that to design and implement a prototype with optimal energy savings named SmartStorage. The system tracks the run-time I/O pattern of a smartphone that is then matched with the closest pattern from the benchmark table. After having obtained the optimal parameters, it dynamically configures storage parameters to reduce energy consumption. We evaluate our prototype by using the 20 most popular Android applications, and our energy-efficient approaches achieve from 23% to 52% of energy savings compared to using the current techniques.

A Software-Based Sonar Ranging Sensor for Smart Phones

We live in a 3-D world. However, the smart phones that we use every day are incapable of sensing depth, without the use of custom hardware. By creating new depth sensors, we can provide developers with the tools that they need to create immersive mobile applications that take advantage of the 3-D nature of our world. In this paper, we propose a new sonar sensor for smart phones. This sonar sensor does not require any additional hardware, and utilizes the phones microphone and rear speaker. The sonar sensor calculates distances by measuring the elapsed time between the initial pulse and its reflection. We evaluate the accuracy of the sonar sensor by using it to measure the distance from the phone to an object. We found that we were able to measure the distances of objects accurately with an error bound of 12 cm.

Smartphone application launch with smarter scheduling

The time it takes to launch a smartphone application is unpredictable. In this paper, we explore how these unpredictable launch times are affected by constraints associated with reading (writing) from (to) flash storage. We conduct the first large-scale measurement study on the Android I/O delay using the data collected from our Android application running on 1480 devices within 188 days. Among others, we observe that reads experience up to 626% slowdown when blocked by concurrent writes. We use this obtained knowledge to design a pilot solution, wherein by prioritizing reads over writes we are able to reduce the launch delay by up to 37.8%.

Evaluating impact of storage on smartphone energy efficiency

We present an experimental study of how storage techniques impact energy consumption in smartphones. We design and implement a system that tracks I/O activities of smartphones in real-time and dynamically changes storage configuration by matching I/O patterns in order to reduce energy consumption. Our system is evaluated on the 20 most popular applications from Android Market, and our results show that the optimal configurations save from 21% to 52% of battery life. We believe that they highlight a new and interesting direction in which the topic of smartphone energy consumption can be further evaluated and expanded upon.

Continuous Authentication With Touch Behavioral Biometrics and Voice on Wearable Glasses

Wearable glasses are on the rising edge of development with great user popularity. However, user data stored on these devices bring privacy risks to the owner. To better protect the owners privacy, a continuous authentication system is needed. In this paper, we propose a continuous and noninvasive authentication system for wearable glasses, named GlassGuard. GlassGuard discriminates the owner and an impostor with behavioral biometrics from six types of touch gestures (single-tap, swipe forward, swipe backward, swipe down, two-finger swipe forward, and two-finger swipe backward) and voice commands, which are all available during normal user interactions. With data collected from 32 users on Google Glass, we show that GlassGuard achieves 99% detection rate and 0.5% false alarm rate after 3.5 user events on average when all types of user events are available with equal probability. Under five typical usage scenarios, the system has a detection rate above 93% and a false alarm rate below 3% after less than five user events.

LBVC: towards low-bandwidth video chat on smartphones

Video chat apps enable users to stay in touch with their family, friends and colleagues. However, they consume a lot of bandwidth and hence can quickly use up a monthly data plan quota, which is a high-cost resource on smartphones. In this paper, we propose LBVC (Low-bandwidth Video Chat), a user-guided vibration-aware frame rate adaption framework. LBVC takes a sender-receiver cooperative approach and reduces bandwidth usage as well as alleviates video quality degradation for video chat apps on smartphones. We implement LBVC on the Android platform and evaluate its performance on a series of experiments and user study with 21 pairs of subjects. Compared to the default solution, LBVC decreases bandwidth usage by 35% and at the same time maintains good video quality without introducing extra power consumption under typical video chat scenarios.

A Context-Aware Framework for Reducing Bandwidth Usage of Mobile Video Chats

Mobile video chat apps offer users an approachable way to communicate with others. As high-speed 4G networks are being deployed worldwide, the number of mobile video chat app users increases. However, video chatting on mobile devices brings users financial concerns, since streaming video demands high bandwidth and can use up a large amount of data in dozens of minutes. Lowering the bandwidth usage of mobile video chats is challenging since video quality may be compromised. In this paper, we attempt to tame this challenge. Technically, we propose a context-aware frame rate adaption framework, named low-bandwidth video chat (LBVC). It follows a sender-receiver cooperative principle that smartly handles the tradeoff between lowering bandwidth usage and maintaining video quality. We implement LBVC by modifying an open-source app-Linphone- and evaluate it with both objective experiments and subjective studies.

All or none? The dilemma of handling WiFi broadcast traffic in smartphone suspend mode

Smartphones save energy by entering a low power suspend mode (<;20mW) when they are idle. We find that on some smartphones, WiFi broadcast frames interrupt suspend mode and force the phone to switch to active mode (>120mW). As a result, power consumption increases dramatically. To improve energy efficiency, some phones employ a hardware broadcast filter in the WiFi driver. All UDP broadcast frames other than Multicast DNS frames are blocked, thus none is received by upper layer applications. So, we have a dilemma of handling WiFi broadcast traffic during smartphone suspend mode: either receive all of them suffering high power consumption, or receive none of them sacrificing functionalities. In this paper, we propose Software Broadcast Filter (SBF) to address the dilemma. SBF is smarter than the hardware broadcast filter as it only filters out useless broadcast frames and does not impair functionalities of applications. SBF is also more energy efficient than the “receive all” method. Our trace driven evaluation shows that SBF can save up to 52% energy consumption than the “receive all” method.

Improving smartphone responsiveness through I/O optimizations

Smartphones suffer various unpredictable delays, e.g., when launching an application. In this work, we investigate the behavior of reads and writes in smartphones. We conduct the first large-scale measurement study on the Android I/O delay using the data collected from our Android application running on 1480 devices within 188 days. Among others, we observe that reads experience up to 626% slowdown when blocked by concurrent writes. We use this obtained knowledge to design a pilot solution that reduces application delays by prioritizing reads over writes. The evaluation shows that our system reduces launch delays by up to 37.8%.